Impacts can inflict critical consequences on composite structures, therefore smart impact monitoring systems can be very helpful. A global optimization of the piezoelectric (PZT) sensors position for impact location identification is investigated in this paper. Artificial Neural Networks (ANNs) and probabilistic analysis approach are used to define the objective function. Genetic algorithms (GAs) are adopted to search for the optimal location of the sensors. Improved crossover and mutation functions are designed. The procedure is applied to a full-scale stiffened composite aircraft panel.
Optimal sensor positioning for impact localization in smart composite panels
MALLARDO, Vincenzo;
2013
Abstract
Impacts can inflict critical consequences on composite structures, therefore smart impact monitoring systems can be very helpful. A global optimization of the piezoelectric (PZT) sensors position for impact location identification is investigated in this paper. Artificial Neural Networks (ANNs) and probabilistic analysis approach are used to define the objective function. Genetic algorithms (GAs) are adopted to search for the optimal location of the sensors. Improved crossover and mutation functions are designed. The procedure is applied to a full-scale stiffened composite aircraft panel.File in questo prodotto:
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